# sklearn.utils.extmath.weighted_mode¶

sklearn.utils.extmath.weighted_mode(a, w, axis=0)[source]

Returns an array of the weighted modal (most common) value in a

If there is more than one such value, only the first is returned. The bin-count for the modal bins is also returned.

This is an extension of the algorithm in scipy.stats.mode.

Parameters
aarray_like

n-dimensional array of which to find mode(s).

warray_like

n-dimensional array of weights for each value

axisint, optional

Axis along which to operate. Default is 0, i.e. the first axis.

Returns
valsndarray

Array of modal values.

scorendarray

Array of weighted counts for each mode.

Examples

>>> from sklearn.utils.extmath import weighted_mode
>>> x = [4, 1, 4, 2, 4, 2]
>>> weights = [1, 1, 1, 1, 1, 1]
>>> weighted_mode(x, weights)
(array([4.]), array([3.]))


The value 4 appears three times: with uniform weights, the result is simply the mode of the distribution.

>>> weights = [1, 3, 0.5, 1.5, 1, 2]  # deweight the 4's
>>> weighted_mode(x, weights)
(array([2.]), array([3.5]))


The value 2 has the highest score: it appears twice with weights of 1.5 and 2: the sum of these is 3.5.